System and methods for early diagnosis of autism spectrum disorders

Abstract

The present disclosure a system and methods for early diagnosis of neurodevelopmental or neurobehavioral diseases, such as autism spectrum disorders (“ASD”). In one aspect, a method for determining a risk for a neonatal patient to develop as ASD is provided. The method includes coupling a sensor assembly comprising plurality of electroencephalogram (“EEG”) sensors to a neonatal patient, and acquiring, using the sensor assembly, EEG data during a sleep state of the neonatal patient. The method also includes analyzing the EEG data to determine neural signatures indicative of a brain activity of the neonatal patient during the sleep state, and generating, based on the neural signatures, a composite representing a neurofunctional profile of the neonatal patient. The method further includes determining a risk for the neonatal patient to develop an autism spectrum disorder (“ASD”) by comparing the composite to a reference, and generating a report indicating the risk.

1 . A method for determining a risk for a neonatal patient to develop an autism spectrum disorder (“ASD”), the method comprising:
 coupling a sensor assembly comprising plurality of electroencephalogram (“EEG”) sensors to a neonatal patient; 
 acquiring, using the sensor assembly, EEG data during a sleep state of the neonatal patient; 
 analyzing the EEG data to determine neural signatures indicative of a brain activity of the neonatal patient during the sleep state; 
 generating, based on the neural signatures, a composite representing a neurofunctional profile of the neonatal patient; 
 determining a risk for the neonatal patient to develop an autism spectrum disorder (“ASD”) by comparing the composite to a reference; and 
 generating a report indicating the risk. 
 
     
     
         2 . The method of  claim 1 , wherein the method further comprises computing, using the EEG data, power spectra associated with different locations about the neonatal patient's head. 
     
     
         3 . The method of  claim 2 , wherein the different locations include a right brain hemisphere and a left brain hemisphere of the neonatal patient. 
     
     
         4 . The method of  claim 3 , wherein the method further comprises computing a difference of spectral power between the right brain hemisphere and the left brain hemisphere. 
     
     
         5 . The method of  claim 1 , wherein the method further comprises computing a coherence between a right brain hemisphere and a left brain hemisphere of the neonatal patient. 
     
     
         6 . The method of  claim 1 , wherein the neural signatures are computed using at least one of a spectral information, a power information, a coherence information, a phase information, a synchrony information, and an asymmetry information. 
     
     
         7 . The method of  claim 1 , wherein an age of the neonatal patient is less than approximately 1 month. 
     
     
         8 . The method of  claim 1 , wherein the composite is generated based on a weighted combination of different neural signatures. 
     
     
         9 . The method of  claim 1 , wherein determining the risk includes utilizing at least one characteristic of the neonatal patient. 
     
     
         10 . A method for determining a likelihood for a neonatal patient to develop a neurobehavioral disease, the method comprising:
 receiving electroencephalogram (“EEG”) data acquired from a neonatal patient during a sleep state;   generating at least one of a spectral power and coherence information using the EEG data;   assembling a neurofunctional profile of the neonatal patient using the at least one of spectral power and coherence information;   correlating the neurofunctional profile with a reference to determine a likelihood for the neonatal patient to develop a neurobehavioral disease; and   generating a report using the likelihood.   
     
     
         11 . The method of  claim 10 , wherein the method further comprises computing, using the EEG data, spectral power associated with different locations about the neonatal patient's head. 
     
     
         12 . The method of  claim 11 , wherein the different locations include a right brain hemisphere and a left brain hemisphere of the neonatal patient. 
     
     
         13 . The method of  claim 12 , wherein the method further comprises computing a difference of spectral power between the right brain hemisphere and the left brain hemisphere. 
     
     
         14 . The method of  claim 10 , wherein the method further comprises computing a coherence between various portions of a right brain hemisphere and a left brain hemisphere of the neonatal patient. 
     
     
         15 . The method of  claim 10 , wherein the method further comprises computing neural signatures using at least one of the spectral power and coherence information to assemble the neurofunctional profile. 
     
     
         16 . The method of  claim 10 , wherein an age of the neonatal patient is less than approximately 1 month. 
     
     
         17 . The method of  claim 10 , wherein the neural profile is generated based on a weighted combination of different neural signatures. 
     
     
         18 . The method of  claim 10 , wherein determining the likelihood includes performing a statistical analysis utilizing at least one characteristic of the neonatal patient. 
     
     
         19 . The method of  claim 10 , wherein determining the likelihood further comprises comparing coherence at multiple frequencies for different locations about the neonatal patient's head. 
     
     
         20 . The method of  claim 19 , wherein the method further comprises comparing coherence values at low frequencies with coherence values at high frequencies.